J Storrs Hall, PhD wrote:
Hmmm. I'd suspect you'd spend all your time and effort organizing the people.
Orgs can grow that fast if they're grocery stores or something else the new
hires already pretty much understand, but I don't see that happening smoothly
in a pure research setting.
I would not be organizing the company: my COO will do that.
My plan is predicated on a particular research approach, and that
research would not be like putting a few hundred "conventional AI"
people together and trying to herd them (I shudder at the thought).
I have a very specific plan already worked out, so I would hire
specialists capable of taking on each component of the work.
In that sense, it would be 10% "research" and 90% implementation. About
exactly the reverse of what you would get in a univiersity AI department.
In fact, the situation is superfically similar to Doug Lenat's approach:
he decided on a plan, then hired people to carry out the specific
plan, with only (I am guessing... Stephen?) 10% research, whil ethe
other 90% was about ontologizing.
I'd claim to be able to do it in 10 years with 30 people with the following
provisos:
1. same 30 people the whole time
2. ten teams of 3: researcher, programmer, systems guy
3. all 30 have IQ > 150
4. big hardware budget, all we build is software
... but I expect that the hardware for a usable body will be there in 10
years, so just buy it.
Project looks like this:
yrs 1-5: getting the basic learning algs worked out and running
yrs 6-10: teaching the robot to walk, manipulate, balance, pour, understand
kitchens, make coffee
It's totally worthless to build a robot that had to be programmed to be able
to make coffee. One that can understand how to do it by watching people do
so, however, is absolutely the key to an extremely valuable level of
intelligence.
100% agreement on that.
Richard Loosemore
Josh
On Friday 08 February 2008 11:46:51 am, Richard Loosemore wrote:
My assumptions are these.
1) A team size (very) approximately as follows:
- Year 1: 10
- Year 2: 10
- Year 3: 100
- Year 4: 300
- Year 5: 800
- Year 6: 2000
- Year 7: 3000
- Year 8: 4000
2) Main Project(s) launched each year:
- Year 1: AI software development environment
- Year 2: AI software development environment
- Year 3: Low-level cognitive mechanism experiments
- Year 4: Global architecture experiments;
Sensorimotor integration
- Year 5: Motivational system and development tests
- Year 6: (continuation of above)
- Year 7: (continuation of above)
- Year 8: Autonomous tests in real world situations
The tests in Year 8 would be heavily supervised, but by that stage it
should be possible for it to get on a bus, go to the suburban home, put
the kettle on (if there was one: if not, go shopping to buy whatever
supplies might be needed), then make the pot of tea (loose leaf of
course: no robot of mine is going to be a barbarian tea-bag user) and
serve it.
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